[HTML][HTML] A comprehensive survey of deep learning in the field of medical imaging and medical natural language processing: Challenges and research directions

B Pandey, DK Pandey, BP Mishra… - Journal of King Saud …, 2022 - Elsevier
The extensive growth of data in the health domain has increased the utility of Deep Learning
in health. Deep learning is a highly advanced successor of artificial neural networks, having …

[HTML][HTML] Social media as a research tool (SMaaRT) for risky behavior analytics: methodological review

T Singh, K Roberts, T Cohen, N Cobb… - JMIR public health …, 2020 - publichealth.jmir.org
Background: Modifiable risky health behaviors, such as tobacco use, excessive alcohol use,
being overweight, lack of physical activity, and unhealthy eating habits, are some of the …

Learn#: A Novel incremental learning method for text classification

G Shan, S Xu, L Yang, S Jia, Y Xiang - Expert Systems with Applications, 2020 - Elsevier
Deep learning is an effective method for extracting the underlying information in text.
However, it performs better on closed datasets and is less effective in real-world scenarios …

[HTML][HTML] Patterns of routes of administration and drug tampering for nonmedical opioid consumption: data mining and content analysis of reddit discussions

D Balsamo, P Bajardi, A Salomone… - Journal of Medical Internet …, 2021 - jmir.org
Background The complex unfolding of the US opioid epidemic in the last 20 years has been
the subject of a large body of medical and pharmacological research, and it has sparked a …

[HTML][HTML] The influence of social media affordances on drug dealer posting behavior across multiple social networking sites (SNS)

MR Haupt, R Cuomo, J Li, M Nali, TK Mackey - Computers in Human …, 2022 - Elsevier
Social media has been documented as widely used for initiating online sales of illicit drugs
such as opioids. However, not much is known about how affordances of social networking …

[HTML][HTML] The adverse effects and nonmedical use of methylphenidate before and after the outbreak of Covid-19: Machine learning analysis

H Shin, CT Yuniar, SA Oh, S Purja, S Park… - Journal of Medical …, 2023 - jmir.org
Background Methylphenidate is an effective first-line treatment for attention-
deficit/hyperactivity disorder (ADHD). However, many adverse effects of methylphenidate …

[HTML][HTML] Discerning conversational context in online health communities for personalized digital behavior change solutions using Pragmatics to Reveal Intent in Social …

T Singh, K Roberts, T Cohen, N Cobb, A Franklin… - Journal of biomedical …, 2023 - Elsevier
Abstract Background Online health communities (OHCs) have emerged as prominent
platforms for behavior modification, and the digitization of online peer interactions has …

Insights from the Twittersphere: a cross-sectional study of public perceptions, usage patterns, and geographical differences of tweets discussing cocaine

C Castillo-Toledo, O Fraile-Martínez… - Frontiers in …, 2024 - frontiersin.org
Introduction Cocaine abuse represents a major public health concern. The social perception
of cocaine has been changing over the decades, a phenomenon closely tied to its patterns …

Effect of feedback on drug consumption disclosures on social media

H Jangra, R Shah, P Kumaraguru - Proceedings of the International …, 2023 - ojs.aaai.org
Deaths due to drug overdose in the US have doubled in the last decade. Drug-related
content on social media has also exploded in the same time frame. The pseudo-anonymous …

Drug abuse detection in twitter-sphere: Graph-based approach

KM Saifuddin, MIK Islam… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
The rate of non-medical use of opioid drugs has increased markedly since the early 2000s.
Due to this non-medical use, abusers suffer from different adverse effects that include …